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Innovate with impact through custom GenAI & ML solutions

86% of companies experiment with GenAI, yet only 21% see meaningful impact. Drive measurable business growth with custom AI solutions and highly efficient agile strategy — and leave your competition behind

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High-speed, low-risk AI prototyping and development

Build and validate AI prototypes and proofs of concepts with lower upfront investment, at double the speed of in-house development. We have the brainpower and expertise to accelerate your AI experiments — and turn the most successful of them into top-tier products.

AI POC in 2–8 weeks

Validate ideas with high-quality AI prototypes and proofs of concepts delivered in 2–8 weeks

Value from day 1

Backed by discovery and architecture support, our experts deliver value from day 1

2X more cost-efficient

Reduce engineering costs with remote teams and get 2X more value on your budget

Prototype, build, and market-test solutions while your competitors are only figuring out their AI strategy

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Certified engineering support for your AI needs

Google Cloud Partner Advantage Program, service partner

Certified information security, cybersecurity, and privacy protection

AWS Certified Solutions Architects and Cloud Practitioners

Certified Azure experts

Your GenAI and ML stack is covered with AI Studio

Artificial intelligence

solutions and expertise

Produce high-quality assets for marketing, sales, communications, product development, and other purposes.

Accelerate and optimize workflows with AI editors, copilots, and assistants tailored to your organization processes and data.

Facilitate customer self-service, enhance user support, and boost engagement with human-like interactions powered by conversational AI.

Summarize, translate, interpret, search through, and extract insights from unstructured, diverse, and multi-format data.

Integrate GenAI into automated reporting to boost speed, granularity, precision, and flexibility.

Create synthetic data for AI/ML model training and data pipeline development and testing.

Key Gen AI technologies

  • Large language models (LLMs)
  • Diffusion models
  • Variational autoencoders
  • Generative adversarial networks
  • Large language models (LLMs)
  • Diffusion models
  • Variational autoencoders
  • Generative adversarial networks

Forecast trends in any industry and at every scale by identifying patterns and outliers in data.

Detect fraudulent activities in financial markets and digital advertising systems.

Identify churn earlier in the customer lifecycle to initiate timely retention campaigns.

Predict traffic accidents, equipment failures, and other risks with accuracy levels exceeding 90%.

Precisely segment audiences and personalize content, services, products, and experiences based on historical data.

Analyze images, videos, and real-world objects ranging in size and scale from crop fields to seaport containers and individual user movements and expressions.

Streamline business processes like predictive inventory management, procurement, supply chain coordination, and more.

Key Predictive AI technologies

  • Neural networks
  • Linear regression
  • Logistic regression
  • Support vector machines
  • Decision trees
  • Random forests
  • K-means clustering
  • Self-trained naive Bayes classifier
  • Neural networks
  • Linear regression
  • Logistic regression
  • Support vector machines
  • Decision trees
  • Random forests
  • K-means clustering
  • Self-trained naive Bayes classifier

Featured case studies:

AI and machine learning

From optimizing Fortune 500 supply chains to predicting subscriber churn at a 28-million-account scale, our AI playbook is all about measurable impact.

AI-driven churn detection for a top TV streaming network

Our AI and Data Studio experts developed a subscriber churn prediction solution leveraged by a premium US television network reaching 28 million American households. The solution enables our client’s marketing team to precisely determine the probability of users leaving the platform based on historical data. The tool leverages a leading-edge cloud infrastructure and a monitoring system preventing model drift and other issues.
Read the full case study

Featured deliverables

  • Churn prediction system based on predictive AI
  • Batch processing for AI/ML model training and analysis
  • Automated monitoring of AI output which enables prevention of issues like bias, hallucinations, model drift, etc.

Technologies

AWS Sagemaker, AWS Batch, XGBoost

AI-driven supply chain analytics leveraged by Fortune 500 brands

One of AgileEngine’s longest-running projects involves the strategic development of a predictive supply chain analytics platform trusted by clients like Dell, Gap, Cisco, and Johnson & Johnson. Our team played a major role in bringing the platform from a prototype to a patented AI/ML product top-listed by Gartner.
Read the full case study

Featured deliverables

  • High-load customer-facing system that tracks cargo and predicts its location and delivery time
  • Processing, ML analytics, and visualization of real-time big data
  • Infrastructure development and optimization of more than 700 microservices
  • Assistance with establishing an effective software development process
  • Software testing, including unit, integration, acceptance, functional, and regression testing

Technologies

Java, Spring, Hibernate, PostgreSQL, Maven, Amazon AWS, Angular 8, Docker, Kafka, Ansible, ELK stack, Apache Superset

AI-powered AdTech trusted by Microsoft, Verizon, and Toyota

A programmatic advertising SaaS trusted by AdAge 100 brands like Microsoft, Audible, and Verizon engages AgileEngine in modernizing its technology platform and product. The solutions introduced by our team are integral to business-critical functionality like campaign audit, analytics, and optimization. Leveraging cutting-edge technology and engineering approaches, our experts re-architected the company’s main API and web apps and developed new AI solutions powering campaign analytics.

Featured deliverables

  • Computer vision model detecting overlaid graphics and text
  • Computer vision model clustering images belonging to the same scene
  • Data labeling process leveraging AWS Sagemaker Ground Truth
  • Model training and optimization on Sagemaker Notebooks and training jobs
  • Deployment as serverless endpoints on the AWS Sagemaker infrastructure
  • R&D experiments involving state-of-the-art models customized with AWS EC2 Instances
  • Collaboration with the client’s product team on planning and the architecture/design of machine learning solutions
  • Design and analysis of metrics for the evaluation of product features and their impact

Technologies

Python, AWS, Amazon Sagemaker, Pytorch, Golang, TypeScript, PHP, Symfony, Laravel, Node.js, Express.js, React.js, Angular.js, Vue.js, Java, Spring, AWS, K8s, CloudFormation, Docker, MySQL, PostgreSQL, Kafka, RabbitMQ, Elasticsearch, Helm, Chrome Headless, MongoDB, Grafana, Prometheus, Kubernetes

AI/ML-powered predictive maintenance for tens of thousands of EVs

AgileEngine creates custom AI and data solutions for an AI startup launched in collaboration with a top-5 luxury car brand featured on the Fortune Global 500 list. The main focus of this collaboration is an ML-as-a-service platform streamlining electric vehicles manufacturing and maintenance. Our team helped ensure that the core AI/ML systems underlying the platform can reliably predict vehicle failures with unparalleled accuracy.

Featured deliverables

  • Machine learning library capturing and analyzing vehicle data
  • Pipelines for the extraction, loading, and transformation of millions of vehicle telemetry records
  • Information management and visualization application
  • Design and deployment of the infrastructure required by Machine Learning models
  • Data visualization enabling the deep analysis of individual vehicles and automotive fleets
  • Alert system enabling the prediction of vehicle failures
  • Built-in analysis tool reducing the manufacturers’ QA time by up to 90%
  • End-to-end software testing
  • UX/UI design improvements

Technologies

Python, AWS, AWS Sagemaker, AWS Glue, MWAA, Redshift, PostgreSQL, Node.js, GraphQL, Serverless Framework,  Prisma ORM, DBT, Terraform, TypeScript, React.js, Vite

You’ll love our deliverables,

take our clients’ word for it

“AgileEngine delivers quality work, much of which can be attributed to their ability to supply such expert resources that fit well with the internal tech stack. They’ve effectively become part of the internal team while providing a good ROI. Responsive and timely, they communicate seamlessly.”

Chris Johnson

CTO, Centriq

“AgileEngine’s developers have adjusted well to the complex software they had little prior experience with. Still, they have performed to a level on par with the in-house developers. They have been eager to learn and contribute, becoming invested in the overall quality of the deliverables.”

Kevin Heidorn

COO, Yobi

“Unlike other providers, AgileEngine offers a competitive price while still doing high-quality work. They focus on building a successful product and not just on getting paid, which fosters a positive working relationship. The team communicates well and is open to changes in project scope.”

Igor Minin

VP of Engineering, iControl

“AgileEngine built a quality product, overcoming communication challenges and several fluctuations in staff. Their CEO’s strong leadership and desire to exceed expectations helps them stand out among other vendors, although clearly defining project ownership is recommended for future endeavors.”

Doug Ramsay

Former Director of Engineering, Livingsocial

Thiago Dutra | VP of Engineering, Americas

Explore AI/ML development strategies with our expert

Talk to Thiago >

Key services

AI/ML solution architecture

  • Technical design and architecture
  • Technology selection and advisory
  • Team assembly
  • Solution and team oversight

Data science

  • Data organization, processing, cleaning, and validation with ML
  • Data analysis
  • ML models design
  • Communication of insights and advisory on solutions

Data/ML engineering

  • Design and development of AI/ML apps and data pipelines
  • Training, retraining, and monitoring of ML systems and models
  • Optimization and enhancement of AI/ML and data solutions, libraries, and frameworks
  • Execution of ML tests and experiments

MLOps and DevOps

  • Shortening and enhancement of the AI/ML development lifecycle
  • Automation and optimization of the work of data/ML engineering, software development, and IT operations
  • Deployment process monitoring and troubleshooting

Our process:

validate ideas in weeks and build impactful solutions

1. Discovery and feasibility analysis
Timeframe: 2–8 hours

Get an AI implementation roadmap based on your challenge and goals, complete with estimates for project duration.
2. Proof of concept and prototyping
Timeframe: 4–8 weeks

Validate your AI product strategy with POC or prototype delivered by a cross-functional team of AI architects, designers, and engineers.
3. Implementation
Timeframe: 2–9 months

Accelerate and automate AI solution deployment while getting 100% transparency regarding team performance and project status.
4. Support
Timeframe: on-demand or continuous

Ensure long-term project success with continuous system testing and adjust ML models to reflect changing market conditions.
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Turn AI into a strategic driver of business growth

Share your AI challenge with our experts and explore the range of solutions we can offer.

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